AI Engineer

We are seeking a hands-on Senior AI Engineer to help design and build advanced AI and agentic applications. This individual will bring strong technical depth in AI/ML, Python, LLMs, and agentic systems and will be responsible for helping shape technical solutions while remaining actively involved in development and implementation., * Design and build AI-powered and agentic applications using Python, LLMs, LangChain, and LangGraph.

• Help define technical solutions and architecture for complex AI and multi-agent workflows.
• Design and implement agent orchestration, including multi-step and multi-turn workflows, tool usage, memory, and interactions between agents and external systems.
• Build and optimize RAG pipelines, including retrieval strategies, embeddings, vector search, and integration with enterprise knowledge sources.
• Contribute to the integration and use of Knowledge Graphs and structured data within AI applications.
• Work with MCP and AI skills/tool integrations to connect AI agents with external applications, APIs, and enterprise systems.
• Apply strong understanding of LLMs and Machine Learning concepts to make informed decisions around model selection, performance, cost, reliability, hallucinations, and guardrails.
• Develop and improve prompt strategies and agent behavior.
• Define and implement approaches for LLM evaluation, AI testing, debugging, and performance optimization.
• Troubleshoot complex AI workflows, including multi-turn conversations, retrieval issues, hallucinations, tool failures, and orchestration challenges.
• Help establish best practices around AI security, data privacy, and responsible AI development.
• Collaborate with engineers and technical teams to translate business problems into scalable AI solutions.

• 10 years of overall experience in Software Engineering, Machine Learning, Data Science, AI Engineering, or a related technical field.
• Strong hands-on programming experience with Python.
• Strong background in Machine Learning, Data Science, or AI/ML concepts.
• Hands-on experience building AI or agentic applications using LLMs.
• Experience with AI agent frameworks such as LangChain and/or LangGraph.
• Experience designing or implementing RAG pipelines.
• Understanding of LLM behavior and limitations, including tokens, context management, hallucinations, guardrails, performance, and cost considerations.
• Experience with prompt engineering and agentic workflows.
• Experience with or strong familiarity with MCP (Model Context Protocol) and AI tool or skills integrations.
• Experience with LLM evaluation, testing, debugging, and optimization.
• Knowledge of NLP concepts and techniques.
• Experience working with APIs and integrating AI applications with external tools and enterprise systems.
• Strong understanding of data privacy and security considerations when developing AI applications.
• Ability to independently analyze technical problems and recommend appropriate AI solutions and designs.

Preferred Skills:

• Experience with multi-agent systems and orchestration.
• Experience with Knowledge Graphs.
• Experience with vector databases, embeddings, and semantic search.
• Experience deploying AI/ML applications in cloud environments.
• Experience building production-grade AI applications in an enterprise environment.